Progression to Uncontrolled Severe Asthma: A Novel Risk Equation.

BACKGROUND: Recently published asthma guidelines by the European Respiratory Society and the American Thoracic Society (ERS-ATS) define severe disease based on medication use and control level. These guidelines also emphasize that asthma severity involves certain biomarker phenotypes, one of them being eosinophilic phenotype. The quantification of the influence of eosinophil level toward predicting disease severity can help decision makers manage therapy better earlier. OBJECTIVE: To develop a risk-scoring algorithm to identify patients at greater risk of developing uncontrolled severe asthma as defined by ERS-ATS guidelines. METHODS: Data on asthma patients were extracted from the EMRClaims + database from January 2004 to July 2011. Patients with continuous enrollment 12 months before and after the date of the first encounter with a diagnosis of asthma (index date) with at least 1 blood eosinophil test result in the 12 months after the index date, but before the development of uncontrolled severe asthma or the study end date, were included. Uncontrolled severe asthma was defined as the first date on which all criteria of the ERS-ATS definition were first satisfied in the 12 months after the index date. Age (≥ 50 years vs. < 50 years), race, and sex were measured at index, and the Charlson Comorbidity Index (CCI) score (> 0 vs. 0) was measured in the pre-index period. Elevated eosinophil level was defined as a test result with ≥ 400 cells/µL. The study cohort was randomly split 50-50 into derivation and validation samples. Cox proportional hazards regression was used to develop the risk score for uncontrolled severe asthma using the derivation cohort with independent variables of eosinophil level, age, sex, race, and CCI. A bootstrapping procedure was used to generate 1,000 samples from the derivation cohort. Variables significant in ≥ 50% of the samples were retained in the final regression model. A risk score was then calculated based on the coefficient estimates of the final model. C-statistic was used to test the model's discrimination power. RESULTS: The study included 2,405 patients, 147 (6%) of whom developed uncontrolled severe asthma. Higher eosinophil level and CCI score > 0 were significantly and independently associated with an increased risk of uncontrolled severe asthma in the derivation cohort (HR = 1.90, 95% CI = 1.17-3.08 and HR = 2.00, 95% CI = 1.28-3.13, respectively); findings were similar in the validation cohort. Total risk score was categorized as 0, 2, and 4. All models showed good C-statistics (0.79-0.80), indicating favorable model discrimination. There was a significantly greater number of patients with uncontrolled severe asthma in the risk score segments of 2 and 4 compared with 0 (each P < 0.0001). CONCLUSIONS: A risk stratification tool using peripheral eosinophil counts and CCI can be used to predict the development of uncontrolled severe asthma. DISCLOSURES: This study was funded by Teva Pharmaceuticals. eMAX Health Systems was a consultant to Teva Pharmaceuticals for this study and received payment from Teva Pharmaceuticals for work on this study. Casciano and Dotiwala are employed by eMAX Health Systems. Krishnan, Li, and Martin received payment from eMAX Health Systems for work on this study. Small was employed by Teva Pharmaceuticals at the time of this study. Study concept and design were contributed primarily by Casciano, Krishnan, Small, and Martin, along with Li and Dotiwala. Dotiwala, Casciano, Small, and Li collected the data, along with Martin and Li and Krishnan. Data interpretation was provided by Martin, Casciano, and Li, with assistance from the other authors. The manuscript was written by Li, Casciano, Dotiwala, and Small, with assistance from the other authors, and revised by Dotiwala, Small, Li, and Martin, with assistance from Krishnan and Casciano.

Burden of asthma with elevated blood eosinophil levels.

BACKGROUND: Asthma is a common chronic condition with an economic burden of almost $56 billion annually in the US. Biologic markers like blood eosinophils, that help predict the risk of exacerbation could help guide more optimal treatment plans and reduce cost. The purpose of this study was to determine whether healthcare resource use and expenditures vary by eosinophil level among patients with asthma. METHODS: Patients with a diagnosis of asthma defined by ICD-9-CM code 493.xx between January 2004 and July 2011 were extracted from EMRClaims + database (eMAX Health, White Plains NY). Patients were classified as mild, moderate, or severe by medication use following diagnosis, based on recommendations of National Institutes of Health Expert Panel Report 3. Patients were classified as those with elevated eosinophils (≥400 cells/µL) and normal eosinophil level (<400 cells/µL). Patients were followed for resource use, defined as hospitalizations, ER visits and outpatient visit and associated costs were calculated to assess whether an economic difference exists between eosinophil groups. Non-parametric tests were used to compare resource use and associated cost between elevated and normal eosinophil groups. Multivariate modeling was performed to assess the contribution of eosinophil level on the likelihood of study outcomes among patients with severe asthma. RESULTS: Among the 2,164 patients meeting eligibility criteria, 1,144 had severity designations. Of these, 179(16 %) of patients had severe asthma of which 20 % (n = 35) had elevated eosinophils. Seventeen percent of patients with elevated eosinophils were admitted to the hospital during the follow-up period, significantly greater than patients with normal eosinophil levels (12 %; p = 0.011). Overall, compared to patients with normal eosinophil levels (n = 1734), patients with elevated eosinophil levels (n = 430) had significantly greater mean annual hospital admissions (0.51 vs. 0.21/year, p = 0.006) and hospital costs (2,536 vs. $1,091, p = 0.011). Logistic regressions showed that elevated eosinophil level was associated with 5.14 times increased odds of all cause admissions (95 % CI:1.76-14.99, p = 0.003) and 4.07 times increased odds of asthma related admissions (95 % CI: 1.26-13.12, p = 0.019). CONCLUSION: Eosinophil elevation was associated with greater healthcare resource use in patients with asthma.

Value of peripheral blood eosinophil markers to predict severity of asthma.

BACKGROUND: Asthma represents a significant clinical and economic burden to the US healthcare system. Along with other clinical manifestations of the disease, elevated sputum and blood eosinophil levels are observed in patients experiencing asthma exacerbations. The aim of this study was to evaluate the association between blood eosinophil levels and asthma severity defined using Expert Panel Report 3 guidelines. METHODS: Patients with asthma diagnosis between 2004 and 2011 were extracted from the EMRClaims+ database (eMAX Health, White Plains, NY) containing electronic medical records linked to insurance claims for over 675,000 patients. The date of first asthma diagnosis was defined as the 'index date'. Patients were required to have at least 1 peripheral eosinophil test (elevated defined as ≥ 400 cells/µL) in the 12 month 'assessment' period following the index date. We classified patients as those with mild asthma and moderate-to-severe asthma based on the pattern of medication use, as recommended by the 2007 National Institutes of Health Expert Panel Report. Logistic regression models were used to determine if patients with moderate-to-severe asthma had increased likelihood of an elevated peripheral eosinophil count, after accounting for demographics and comorbidities. RESULTS: Among 1,144 patients with an asthma diagnosis, 60 % were classified as having moderate-to-severe asthma. Twenty four percent of patients with moderate-to-severe asthma and 19 % of patients with mild asthma had an elevated peripheral eosinophil count (p = 0.053). Logistic regression showed that moderate-to-severe asthma was associated with 38 % increased odds of elevated eosinophil level (OR 1.38, 95 % CI: 1.02 to 1.86, p = 0.04). CONCLUSION: Patients with moderate-severe asthma are significantly more likely to have an elevated peripheral eosinophil count than patients with mild asthma.

Blood eosinophil count and prospective annual asthma disease burden: a UK cohort study.

BACKGROUND: Elevated sputum eosinophil counts predict asthma exacerbations and responsiveness to inhaled corticosteroids but are impractical to measure in primary care. We investigated the relation between blood eosinophil count and prospective annual asthma outcomes for a large UK cohort. METHODS: This historical cohort study used anonymised medical record data to identify primary care patients with asthma aged 12-80 years with 2 years of continuous records, including 1 year before (baseline) and 1 year after (outcome) their most recent eosinophil count. Negative binomial regression was used to compare outcome exacerbation rates and logistic regression to compare odds of asthma control for patients with blood eosinophil counts of 400 cells per µL or less versus greater than 400 cells per µL, adjusting for age, sex, body-mass index, smoking status, and Charlson comorbidity index. The study is registered at ClinicalTrials.gov, number NCT02140541. FINDINGS: Overall, 20 929 (16%) of 130 248 patients had blood eosinophil counts greater than 400 cells per µL. During the outcome year, these patients experienced significantly more severe exacerbations (adjusted rate ratio [RR] 1·42, 95% CI 1·36-1·47) and acute respiratory events (RR 1·28, 1·24-1·33) than those with counts of 400 cells per µL or less. They also had significantly lower odds of achieving overall asthma control (OR 0·74, 95% CI 0·72-0·77), defined as limited reliever use and no asthma-related hospital attendance or admission, acute course of oral corticosteroids, or prescription for antibiotics. Exacerbation rates increased progressively with nine ascending categories of blood eosinophil count as compared with a reference category of 200 cells per µL or less. INTERPRETATION: Patients with asthma and blood eosinophil counts greater than 400 cells per µL experience more severe exacerbations and have poorer asthma control. Furthermore, a count-response relation exists between blood eosinophil counts and asthma-related outcomes. Blood eosinophil counts could add predictive value to Global Initiative for Asthma control-based risk assessment. FUNDING: Teva Pharmaceuticals.